Yaoqing Yang | DeepAI

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Featured Co-authors

Michael W. Mahoney
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Prateek Mittal
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Kannan Ramchandran
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Kevin Swersky
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∙ 05/28/2023

A Three-regime Model of Network Pruning

Recent work has highlighted the complex influence training hyperparamete...

0 Yefan Zhou, et al. ∙

∙ 05/21/2023

When are ensembles really effective?

Ensembling has a long history in statistical data analysis, with many im...

0 Ryan Theisen, et al. ∙

∙ 06/12/2022

Neurotoxin: Durable Backdoors in Federated Learning

Due to their decentralized nature, federated learning (FL) systems have ...

0 Zhengming Zhang, et al. ∙

∙ 02/06/2022

Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data

The search for effective and robust generalization metrics has been the ...

3 Yaoqing Yang, et al. ∙

∙ 12/08/2021

The Effect of Model Size on Worst-Group Generalization

Overparameterization is shown to result in poor test accuracy on rare su...

4 Alan Pham, et al. ∙

∙ 11/30/2021

A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks

Neural networks (NN) for single-view 3D reconstruction (SVR) have gained...

0 Yefan Zhou, et al. ∙

∙ 11/05/2021

Augmentations in Graph Contrastive Learning: Current Methodological Flaws Towards Better Practices

Graph classification has applications in bioinformatics, social sciences...

0 Puja Trivedi, et al. ∙

∙ 07/23/2021

Taxonomizing local versus global structure in neural network loss landscapes

Viewing neural network models in terms of their loss landscapes has a lo...

9 Yaoqing Yang, et al. ∙

∙ 04/27/2021

Contrastive Spatial Reasoning on Multi-View Line Drawings

Spatial reasoning on multi-view line drawings by state-of-the-art superv...

10 Siyuan Xiang, et al. ∙

∙ 02/12/2021

Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks

Most graph neural networks (GNN) perform poorly in graphs where neighbor...

0 Yujun Yan, et al. ∙

∙ 08/26/2020

Benchmarking Semi-supervised Federated Learning

Federated learning promises to use the computational power of edge devic...

15 Zhengming Zhang, et al. ∙

∙ 07/09/2020

Boundary thickness and robustness in learning models

Robustness of machine learning models to various adversarial and non-adv...

14 Yaoqing Yang, et al. ∙

∙ 01/21/2020

Serverless Straggler Mitigation using Local Error-Correcting Codes

Inexpensive cloud services, such as serverless computing, are often vuln...

0 Vipul Gupta, et al. ∙

∙ 05/11/2019

Deep Unsupervised Learning of 3D Point Clouds via Graph Topology Inference and Filtering

We propose a deep autoencoder with graph topology inference and filterin...

0 Siheng Chen, et al. ∙

∙ 12/16/2018

Coded Elastic Computing

Cloud providers have recently introduced low-priority machines to reduce...

0 Yaoqing Yang, et al. ∙

∙ 11/28/2018

An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation

We propose a novel application of coded computing to the problem of the ...

0 Utsav Sheth, et al. ∙

∙ 06/15/2018

Straggler-Resilient and Communication-Efficient Distributed Iterative Linear Solver

We propose a novel distributed iterative linear inverse solver method. O...

0 Farzin Haddadpour, et al. ∙

∙ 05/15/2018

Coded Iterative Computing using Substitute Decoding

In this paper, we propose a new coded computing technique called "substi...

0 Yaoqing Yang, et al. ∙

∙ 12/19/2017

FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds

Recent deep networks that directly handle points in a point set, e.g., P...

0 Yaoqing Yang, et al. ∙

∙ 12/19/2017

Neighbors Do Help: Deeply Exploiting Local Structures of Point Clouds

Unlike on images, semantic learning on 3D point clouds using a deep netw...

0 Yiru Shen, et al. ∙